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Delving into the design and justification of inscrutable algorithms. Pioneering approaches to making AI systems more transparent and understandable, fostering trust and acceptance among their users.
Analyzing ethical considerations in eHealth digitalization projects. Designing digital health systems that prioritize patient welfare, data privacy, and fairness while aligning with ethical and legal standards.
Evaluating the impact of automated decision-making in public sectors. Providing tools and frameworks, such as the developed impact assessment tool, to ensure the trustworthy application of these systems in public services and companies.
Delving into and understanding fairness within Machine Learning tools and models, with a specific focus on applications in the Insurance and Health sectors. The aim is to explore methods that ensure balanced machine learning applications that cater to a diverse population and prevent unintentional biases, especially in decisions related to healthcare and insurance policies.
Working closely with NGOs like AlgorithmWatch, exploring the potential risks large platforms pose to democratic systems. Offering methodologies to identify these risks and proposing measures to ensure that the digital platforms uphold the principles of a democratic society.
Collaborating with AlgorithmWatch and Canton Zurich, developing tools and guidelines for evaluating the implications of automated decision systems in public administration. This work ensures that public entities adopt these technologies responsibly, maintaining transparency and fairness.
The complete collection of business reports
The complete collection of business reports
The complete collection of my publications by categories: journals, conference proceedings, books, and book chapters
The complete collection of my publications by categories: journals, conference proceedings, books, and book chapters
